Search Results (8,543)

Access to practice opportunities for history-taking in undergraduate medical education can be resource-limited. Large language models are a potential avenue to address this. This study sought to characterize changes in learner self-reported confidence with history-taking before and after a simulation with an LLM-based patient and understand learner experience with and the acceptability of virtual LLM-based patients. This was a multi-method study conducted at McMaster University. Simulations were facilitated with the OSCEai tool. Data was collected through surveys with a Likert scale and open-ended questions and semi-structured interviews. A total of 24 participants generated 93 survey responses and 17 interviews. Overall, participants reported a 14.6% increase in comfort with history-taking. Strengths included its flexibility, accessibility, detailed feedback, and ability to provide a judgement-free space to practice. Limitations included its lower fidelity compared to standardized patients and at times repetitive and less clinically relevant feedback as compared to preceptors. It was overall viewed best as a supplement rather than a replacement for standardized patients. In conclusion, LLM-based virtual patients were feasible and valued as an adjunct tool. They can support scalable, personalized practice. Future work is needed to understand objective metrics of improvement and to design curricular strategies for integration. Full article

Learning and understanding of art are increasingly understood as dynamic processes in which emotion and cognition unfold over time. However, classroom-based evidence on how structured temporal intervals and guided prompts reshape students’ emotional experience remains limited. This study addresses these gaps by quantitatively examining changes in emotion over time in a higher education institution. Employing a comparative experimental design, third-year undergraduate art students participated in two structured courses, where emotional responses were captured using an emotion recognition approach (facial expression and self-reported text) during two sessions: initial impression and delayed impression (three days later). The findings reveal a high consistency in dominant facial expressions and substantial agreement in self-reported emotions across both settings. However, the delayed impression elicited greater emotional diversity and intensity, reflecting deeper cognitive engagement and emotional processing over time. These results reveal a longitudinal trajectory of emotion influenced by guided reflective re-view over time. Emotional dynamics extend medium theory by embedding temporal and affective dimensions into TBMA course settings. This study proposes an ethically grounded and technically feasible framework for emotion recognition that supports reflective learning rather than mere measurement. Together, these contributions redefine TBMA education as a temporal and emotional ecosystem and provide an empirical foundation for future research on how emotion fosters understanding, interest, and appreciation in higher media art education. Full article

Background/Objectives: Precautionary health behaviours (PHBs), such as hand-washing or self-isolation, are non-pharmaceutical interventions used to reduce SARS-CoV-2 transmission. We investigated the potential confounding by PHBs of COVID-19 vaccine effectiveness (VE) estimates in a subset of study participants enrolled in id.DRIVE. Methods: The id.DRIVE COVID-19 VE study (formerly COVIDRIVE) is a European multicentre test-negative case–control study estimating COVID-19 VE against hospitalisation due to laboratory-confirmed SARS-CoV-2 in patients with severe acute respiratory infection. All adults (≥18 y) prospectively enrolled between 16 November 2021 and 16 August 2023 at three sites were invited to complete a PHB survey capturing indicators of PHBs in the 3 months preceding admission. Fisher’s exact test with Bonferroni-adjusted threshold was used to measure the level of association between PHB indicators and both COVID-19 vaccine status and SARS-CoV-2 test result. VE estimates were generated with and without adjustment for PHBs. Results: PHBs were modified over time, with higher precautionary attitudes in the first COVID-19 vaccine booster season (2021–2022) compared to the second one (2022–2023). For the first booster season, PHBs were positively associated with exposures (vaccination status) and outcomes (case or control status). Adjusting for PHBs led to a 6 to 9 percentage-point increase in VE estimates. Conversely, no confounding by PHBs was observed in the second booster season. Conclusions: PHBs should be considered a possible confounder of COVID-19 VE studies. Further research is needed to define when PHBs should be integrated into VE models, as the level of confounding may differ according to the study population and the epidemiological context. Full article

Background/Objectives: Workplace violence remains an important vocational psycho-social risk for nurses employed in the emergency department (ED). We investigated the characteristics of workplace violence against ED nurses, and associations with self-assessed resilience, socio-demographic and vocational parameters, including turnover intention. Methods: ED nurses employed in all public hospitals in the Republic of Cyprus (RC) participated. After obtaining informed consent, data were collected using census sampling (January–June 2024) via the translated 2016 Italian National Survey on Violence towards Emergency Nurses Questionnaire (QuINVIP16) for investigating workplace violence characteristics, and the Connor-Davidson Resilience Scale (CD-RISC-25) for assessing self-perceived resilience. Results: A total of 132 nurses (53.0% response rate) participated. Verbal violence was reported by 70.5% to 92.4% of participants. Long waiting times, overcrowded EDs, and perception of inadequate attention from healthcare professionals were reported as the primary triggers for violence towards participants by patients/visitors. One-third of participants reported that violence-reporting systems were unclear, while 1 out of 4 reported inadequate safety measures against violence. Participants with higher scores of self-perceived resilience were less likely to report turnover intention due to workplace violence (p < 0.001), while those with lower self-perceived resilience reported a significant decrease in work motivation (p = 0.005). Those who experienced decreased work motivation after exposure to a violent episode were more likely to consider a) leaving the profession [OR (95%CI): 79.1(17.7–353.2); p < 0.01], and b) moving to a different work setting [OR (95%CI): 17.0(3.8–76.2); p < 0.01], and actually applying to be transferred to a different work setting [OR (95%CI): 19.6(4.2–91.5); p < 0.01]. Moreover, those who had not attended communication skills training were 4 times more likely to consider leaving the profession following exposure to violence [OR (95%CI): 4.2(1.1–16.2); p = 0.04]. Conclusions: This study is among the few to link workplace violence with both resilience and actual turnover behaviors among emergency nurses, in general and particularly in the post-pandemic era. By showing how personal resilience in the face of violence is shaped by organizational support, such as reporting systems and training, the present findings move beyond individuals-level explanations, and highlight workplace violence as a systematic administrative challenge. This insight represents an important advance in current knowledge, and calls for multifaceted interventions that strengthen both personal and institutional capacity to address violence. Full article

Microbiologically Influenced Corrosion (MIC) significantly endangers steel infrastructure, particularly in marine and buried environments, causing considerable economic and environmental damage. Sulphate-reducing bacteria (SRB) are primary supporters of MIC, accelerating iron corrosion through hydrogen sulfide production. Conventional mitigation strategies, including protective coatings and cathodic protection, often face challenges such as limited effectiveness against SRB and the aggressiveness of saltwater corrosion. This study explores a novel approach by directly introducing zinc oxide (ZnO) nanoparticles into the microbial medium to inhibit SRB activity and reduce MIC. Iron metal coupons were immersed in seawater under three conditions: control (seawater only), seawater with SRB, and SRB with ZnO nanoparticles. These coupons were used as electrodes in microbial fuel cells to obtain real-time voltage readings. At the same time, corrosion was evaluated using cyclic voltammetry (CV), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), mass loss, and pH measurements. Results demonstrate that ZnO nanoparticles significantly inhibited SRB growth, as confirmed by the antibiotic susceptibility test (ABST). It was revealed that the corrosion rate increased by 21.3% in the presence of SRB compared to the control, whereas the ZnO-added electrode showed a 21.7% reduction in corrosion rate relative to the control. SEM showed prominent corrosive products on SRB-exposed coupons. ZnO-added coupons exhibited a protective layer with grass-like whisker structures, and EDX results confirmed reduced sulfur and iron sulfide deposits, indicating suppressed SRB metabolic activity. ABST confirmed ZnO’s antimicrobial properties by producing clear inhibition zones. ZnO nanoparticles offer the dual benefits of antimicrobial activity and corrosion resistance by forming protective self-coatings and inhibiting microbial growth, making them a scalable and eco-friendly alternative to traditional corrosion inhibitors. This application can significantly extend the lifespan of iron structures, particularly in environments prone to microbial corrosion, demonstrating the potential of nanomaterials in combating microbiologically influenced corrosion (MIC). Full article

Swimming pools, symbols of luxury in tourism-driven Greece, raise concerns about water consumption in water-scarce regions. This study assesses their hydrological impact in two regions of Southern Greece, West Mani (Peloponnese) and Naxos Island (Cyclades), within the water–energy–food nexus framework, evaluating the resulting trade-offs. Using satellite imagery, we identified 354 pools in West Mani (11,738 m²) and 556 in Naxos (26,825 m²). Two operational scenarios were evaluated: complete seasonal emptying and refilling (Scenario 1) and one-third annual water renewal (Scenario 2). Annual water use ranged from 39,000 to 51,000 m³ in West Mani and 98,000 to 124,000 m³ in Naxos—equivalent to the needs of 625–2769 and 1549–6790 people in West Mani and Naxos, respectively. In Naxos, this volume could alternatively irrigate 27–40 hectares of potatoes, producing food for 700–1500 people. Energy requirements, particularly where desalination is used, further increase the burden, with Naxos pools requiring 384–846 MWh annually. Although swimming pools are highly visible water consumers, their overall contribution to water scarcity is modest compared to household and agricultural uses. Their visibility, however, amplifies public concern. Rainwater harvesting, requiring collection areas 10–24 times larger than pool surface areas, especially in residential and hotel settings, could make pools largely self-sufficient. Integrating such measures into water management and tourism policy can help balance luxury amenities with resource conservation in water-scarce Mediterranean regions. Full article

Background/Objectives: There is a growing need for programs addressing perinatal mental health, particularly for new mothers. Postpartum depression (PPD) may occur during pregnancy or within the first year postpartum, with both short- and long-term negative consequences for both mothers and their infants. This study describes the cultural adaptation, implementation, and one-year follow-up of the Mom-to-Mom (M2M) program for minority Bedouin women in Southern Israel. Methods: We conducted a community-based intervention (M2M) emphasizing cultural adaptation. Outreach efforts were conducted in collaboration with healthcare professionals to encourage referral to the M2M program. A total of 111 mothers completed a self-administered questionnaire that included socio-demographic characteristics and PPD symptoms (PPDs) at two time points: prior to the intervention (Time-1) and one year after participating in the program (Time-2). PPD was measured using the Edinburgh Postnatal Depression Scale (EPDS), using a score cutoff of ≥10. Results: There was a significant decrease in PPDs (EPDS ≥ 13) between Time-1 and Time-2 after one year of follow-up in the M2M program (from 45% to 19.8%). Of the participants, 75% were referred to the program by healthcare professionals. Among those with EPDS ≥ 10, 30% were referred to mental health services. This program provided education, professional support, and led to the establishment of the first M2M center within a Bedouin community, located in the Negev (Naqab). Conclusions: The results emphasize the importance of culturally sensitive approaches to increase awareness, early diagnosis, and professional support in addressing PPD, tailored to a cultural context. Culturally adapted programs can be effective in minority populations and contribute to reducing disparities in maternal mental health care. Full article

Collaborative Online International Learning (COIL) has become an innovative pedagogical strategy that promotes the internationalization of curricula and the development of transversal competencies. In architecture, its implementation is particularly relevant because there is a growing need to train professionals capable of leading and collaborating in global and interdisciplinary contexts. However, evidence of COIL’s impact during the early stages of higher education in Latin America remains limited. This study analyzed the experience of 39 architecture students from the Universidad Nacional de San Agustín de Arequipa (Peru), who collaborated with peers from Mexico in a five-week COIL project focused on design methodologies for vulnerable populations. Using a mixed-methods approach, the study assessed students’ competencies in leadership, self-regulation in virtual learning, and emotional intelligence and teamwork through pre- and post-experience questionnaires complemented with open-ended questions. Findings indicate that although students’ self-perceptions of their competencies remained at medium-to-high levels overall, changes occurred differently among groups: students with initially low self-assessment scores showed improvements, whereas those with initially high scores tended to moderate their self-assessment. Qualitative analysis highlighted barriers such as limited communication, time zone differences, and unequal participation. Overall, the results suggest that the COIL experience not only supported the development of competencies but also fostered critical reflection and a more realistic self-assessment of students’ competencies in virtual and intercultural contexts. Full article

Accurate classification between magnetizing inrush currents and internal faults is essential for reliable transformer protection and stable power system operation. Because their transient waveforms are so similar, conventional differential protection and harmonic restraint techniques often fail under dynamic conditions. This study presents a two-stage classification model that combines a self-organizing map (SOM) and a convolutional neural network (CNN) to enhance robustness and accuracy in distinguishing between inrush currents and internal faults in power transformers. In the first stage, an unsupervised SOM identifies topologically structured event clusters without the need for labeled data or predefined thresholds. Seven features are extracted from differential current signals to form fixed-length input vectors. These vectors are projected onto a two-dimensional SOM grid to capture inrush and fault distributions. In the second stage, the SOM’s activation maps are converted to grayscale images and classified by a CNN, thereby merging the interpretability of clustering with the performance of deep learning. Simulation data from a 154 kV MATLAB/Simulink transformer model includes inrush, internal fault, and overlapping events. Results show that after one cycle following fault inception, the proposed method improves accuracy (AC), precision (PR), recall (RC), and F1-score (F1s) by up to 3% compared with a conventional CNN model, demonstrating its suitability for real-time transformer protection. Full article

Accurate short-term photovoltaic (PV) power generation forecasting is critical for the stable integration of renewable energy into the grid. This study proposes a Transformer model enhanced with an adaptive sparse self-attention (ASSA) mechanism for PV power forecasting. The ASSA framework employs a dual-branch attention structure that combines sparse and dense attention paths with adaptive weighting to effectively filter noise while preserving essential spatiotemporal features. This design addresses the critical issues of computational redundancy and noise amplification in standard self-attention by adaptively filtering irrelevant interactions while maintaining global dependencies in Transformer-based PV forecasting. In addition, a deep feedforward network and a feature refinement feedforward network (FRFN) adapted from the ASSA–Transformer are incorporated to further improve feature extraction. The proposed algorithms are evaluated using time-series data from the Desert Knowledge Australia Solar Centre (DKASC), with input features including temperature, relative humidity, and other environmental variables. Comprehensive experiments demonstrate that the ASSA models’ accuracy in short-term PV power forecasting increases with longer forecast horizons. For 1 h ahead forecasts, it achieves an R${}^2$ of 0.9115, outperforming all other models. Under challenging rainfall conditions, the model maintains a high prediction accuracy, with an R${}^2$ of 0.7463, a mean absolute error of 0.4416, and a root mean square error of 0.6767, surpassing all compared models. The ASSA attention mechanism enhances the accuracy and stability in short-term PV power forecasting with minimal computational overhead, increasing the training time by only 1.2% compared to that for the standard Transformer. Full article

Objectives: Hearing aids (HAs) are the most common intervention recommended for hearing loss (HL). Many adults with HL do not seek HA rehabilitation. Several studies have attempted to identify barriers and facilitators to using HAs. Different bureaucratic processes for acquiring HAs may lead to different barriers and facilitators. In addition, studies have not yet explored the factors influencing compliance with a recommendation for an HA consultation. This study focuses on the stage prior to consultation in a context where HAs are heavily subsidized. Methods: 148 patients who had undergone a hearing test during 2022 at Hadassah University Medical Center and received a recommendation to undergo a hearing aid consultation were contacted for a telephone survey. Seventy-two adults, 48 male and 24 female, aged 25–85 years, with HL ranging from slight to profound, responded to a telephone questionnaire. The questionnaire, based on two previously published English questionnaires and translated and adapted into Hebrew, was used to assess the main reasons a person did or did not comply with the recommendation to pursue an HA consultation. Results: HL was more severe in those who sought hearing rehabilitation. The main reasons for seeking hearing rehabilitation are the need and desire to hear better and pressure from others. The foremost reasons for not pursuing hearing rehabilitation are feeling that there is currently no need, esthetics, lack of time, and self-consciousness. No significant gender- or age-based differences were found. Conclusions: There are additional barriers to seeking HAs aside from cost and accessibility. Understanding the reasons for avoidance of hearing rehabilitation may help in developing strategies that encourage people to seek hearing rehabilitation and use HAs when the need exists. Full article

The COVID-19 pandemic has placed a considerable psychological burden on healthcare workers, potentially leading to increased burnout and anxiety. This study aimed to evaluate burnout and anxiety levels among healthcare workers compared to non-healthcare professionals during the pandemic. We initially recruited 438 adults; 351 (217 HCWs and 134 non-HCWs) provided complete responses across all three survey waves and were analyzed. Burnout was assessed using the Maslach Burnout Inventory, and anxiety with the State–Trait Anxiety Inventory. Data were collected through an online self-administered survey at three different time points during the pandemic, and analyzed with non-parametric tests and effect sizes. Healthcare workers exhibited significantly higher levels of emotional exhaustion, depersonalization, overall burnout, and anxiety compared to non-healthcare workers across all three periods (p < 0.05). Of 438 consented individuals, 351 (80.1%) completed all waves, allowing within-population longitudinal comparisons. Within the healthcare worker group, women, individuals living alone, those working night shifts, and those considering a career change had notably higher burnout and anxiety scores. No significant differences were observed in personal accomplishment scores. Healthcare workers experienced greater psychological distress than non-healthcare workers during the COVID-19 pandemic. Identifying vulnerable subgroups and implementing supportive strategies are essential to protect the mental health and well-being of healthcare professionals during pandemics and similar crises. Full article

Coastal zones, as critical intersections of ecosystems, resource utilization, and socioeconomic activities, exhibit complex and diverse land cover types with frequent changes. Acquiring large-scale, high-quality annotated data in these areas is costly and time-consuming, which makes rule-based segmentation methods reliant on extensive annotations impractical. Few-shot semantic segmentation, which enables effective generalization from limited labeled samples, thus becomes essential for coastal region analysis. In this work, we propose an optimized few-shot segmentation method based on the Segment Anything Model (SAM) with a frozen-parameter segmentation backbone to improve generalization. To address the high visual similarity among coastal vegetation classes, we design a cross-matching module integrated with a hyper-correlation pyramid to enhance fine-grained visual correspondence. Additionally, a self-matching module is introduced to mitigate scale variations caused by UAV altitude changes. Furthermore, we construct a novel few-shot segmentation dataset, OUC-UAV-SEG-$2^{\mathrm{i}}$, based on the OUC-UAV-SEG dataset, to alleviate data scarcity. In quantitative experiments, the suggested approach outperforms existing models in mIoU and FB-IoU under ResNet50/101 (e.g., ResNet50’s 1-shot/5-shot mIoU rises by 4.69% and 4.50% vs. SOTA), and an ablation study shows adding CMM, SMM, and SAM boosts Mean mIoU by 4.69% over the original HSNet, significantly improving few-shot semantic segmentation performance. Full article

The present study aimed to evaluate the effect of maternal involvement in children’s home-based learning activities during the COVID-19 lockdown on mothers’ parenting stress, the quality of maternal care perceived by offspring, and the level of children’s internalizing/externalizing symptoms. This study recruited 415 subjects from the general population. To assess parenting stress, mothers were administered the Parenting Stress Index–Short Form; to assess children’s perceived quality of maternal care, this study used the Parental Bonding Inventory; and the Child Behavior Checklist/6–18 was used to assess internalizing/externalizing symptoms in children. Correlations showed that the amount of time spent by the mother supervising children’s self-study was highly and positively correlated with parental stress and offspring’s externalizing (but not internalizing) symptoms, and highly and positively correlated with the subscale of maternal overprotection in the children’s perceived quality of maternal care. Moreover, the multiple regression analyses conducted based on the above significant correlations showed that the amount of time spent by the mother overseeing children’s study was associated with parental stress, children’s externalizing symptoms, and maternal overprotection. Overall, the current study contributes to showing the burden families had to face as a result of school closures and accompanying distance learning during the COVID-19 epidemic. Full article

(1) Background: Fiberoptic Endoscopic Evaluation of Swallowing (FEES) is one of the two gold-standard tools for assessing oropharyngeal dysphagia (alongside Videofluoroscopic Swallowing Study). Although generally considered safe, concerns about complications persist, particularly in systems where FEES is not routine and professional roles differ. The aim of this study was to evaluate the safety of FEES performed by both speech-language pathologists (SLPs) and physicians, in order to provide evidence of its safety in a healthcare system where the procedure is not yet widely established and to identify patient subgroups potentially at higher risk of procedure-related complications. (2) Methods: This retrospective study analyzed 964 consecutive FEES procedures. Examinations were carried out by trained SLPs or physicians. Data included demographics, clinical status, operator qualifications, setting, and complications, classified as minor (vomiting, poor tolerance, early termination) or major (laryngospasm, epistaxis). (3) Results: The overall complication rate was 1.14% (11/964): 0.6% minor and 0.5% major. All events were self-limiting. Complication rates did not differ between SLPs (1.05%) and physicians (1.23%) or by experience, setting, drug use, penetration–aspiration scale score, or nasogastric tube. Four complications occurred in amyotrophic lateral sclerosis patients, suggesting higher risk. (4) Conclusions: FEES is safe and well tolerated when performed by either physicians or SLPs. These findings underscore the value of task sharing in dysphagia diagnostics, demonstrating that a shared model increases service capacity, reduces delays, and facilitates timely management of dysphagia. Full article